In statistics, absolute error is essentially a measurement of how much error is present in your calculations. Absolute error is the difference between the actual measured value and the true, accurate value.
For example, if you weigh your dog on a scale and the scale says 30 pounds but you know definitively your dog weighs 27 pounds the scale has an absolute error of 3 pounds (30-27=3). Absolute error is akin to the concept of absolute value that we learned in algebra: the positive number of difference between two values (positive or negative). I.e. |+2| + |-2| = 4. The mean absolute error (MAE) measures the difference between two continuous variables. This means the measurement of differences (if any) between two variables when measured across a distance (time or physical).